Abstract
Efficient scheduling methods are essential for time and cost reduction in grid workflow applications, depicted by directed acyclic graphs (DAG). Few of the proposed algorithms consider users’ demands when allocating tasks to heterogeneous resources with different capabilities and costs. In this paper, a dynamic time and cost tradeoff heuristic is presented to optimize the cost and time of the whole workflow. The algorithm identifies the time-critical activities and cost-critical activities in each ready list generated during the workflow execution. Appropriate services are allocated to time-critical and cost-critical activities based on different QoS criteria. Experimental results show that the algorithm can achieve a better tradeoff between workflow completion time and execution cost.
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Yuan, Y., Li, X., Wang, Q. (2007). Dynamic Heuristics for Time and Cost Reduction in Grid Workflows. In: Shen, W., Luo, J., Lin, Z., Barthès, JP.A., Hao, Q. (eds) Computer Supported Cooperative Work in Design III. CSCWD 2006. Lecture Notes in Computer Science, vol 4402. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72863-4_51
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DOI: https://doi.org/10.1007/978-3-540-72863-4_51
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72862-7
Online ISBN: 978-3-540-72863-4
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